The objective of the proposed research is to facilitate the identification of patient safety hazards by developing advanced visualization tools with automated trend identification algorithms to support the analysis of large patient safety incident databases. The cognitive and information needs of patient safety leaders that are responsible for analyzing patient safety event data will be studied. This knowledge will be leveraged, in combination with principles from data analytics and visualization science, to design and develop analysis tools that fit the needs of these leaders. The prototype tools will be evaluated with the patient safety leaders to determine their effectiveness. This project utilizes the extensive expertise of the research team in human factors and safety science, usability, data analytics, and visualization. Contributions from this research will include a fundamental understanding of the critical user needs of patient safety leaders that analyze patient safety event data from incident reporting systems. The tools developed will facilitate the analysis of these data and will improve patient safety by helping identify patient safety hazards in large incident databases. The rapid identification of hazards will allow for process improvements to improve patient care.